Data Science Concepts

Data Science Concepts

1. What is data science?

   • Data science is a multidisciplinary field that combines techniques from statistics, computer science, and domain knowledge to extract valuable insights and knowledge from data. It encompasses data collection, data cleaning, data analysis, machine learning, and data visualization to solve complex problems and make data-driven decisions. Data science often serves as the foundation for data analytics.

2. 6 Phases CRISP DM Methodology

   • 1. Business understanding
   • 2. Data understanding
   • 3. Data preparation
   • 4. Data modeling
   • 5. Evaluation
   • 6. Deployment

3. What is data analytics?

   • Data analytics is the process of examining and interpreting data to uncover meaningful insights, patterns, and trends. It involves collecting, cleaning, and analyzing data to make informed decisions and solve problems.

4. What is big data?

   • The Big Data concept refers to massive and often unstructured data, in which the processing capabilities of traditional data management tools turn out to be inadequate. Big Data can take up terabytes and petabytes of storage space in a variety of formats, including text, video, sound, images, and more.

5. "The Big Short" and "Margin Call" Connection to Data Science

   • Risk Assessment
     • Identify financial risks through data analysis
   • Data Analysis
     • Analyze financial data to detect patterns.
   • Machine Learning
     • Use predictive models for market trends.
   • Data Visualization
     • Communicate insights with charts and graphs.